{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:27:37Z","timestamp":1760243257288,"version":"build-2065373602"},"reference-count":70,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2014,6,11]],"date-time":"2014-06-11T00:00:00Z","timestamp":1402444800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Forests"],"abstract":"<jats:p>The availability of images with very high spatial and spectral resolution from airborne sensors or those aboard satellites is opening new possibilities for the analysis of fine-scale vegetation, such as the identification and classification of individual tree species. To evaluate the potential of these images, a study was carried out to compare the spatial, spectral and temporal resolution between QuickBird and ADS40-SH52 imagery, in order to discriminate and identify, within the mixed Mediterranean forest, individuals of the Iberian wild pear (Pyrus bourgaeana). This is a typical species of the Mediterranean forest, but its biology and ecology are still poorly known. The images were subjected to different correction processes and data were homogenized. Vegetation classes and individual trees were identified on the images, which were classified from two types of supervised classification (Maximum Likelihood and Support Vector Machines) on a pixel-by-pixel basis. The classification values were satisfactory. The classifiers were compared, and Support Vector Machines was the algorithm that provided the best results in terms of overall accuracy. The QuickBird image showed higher overall accuracy (86.16%) when the Support Vector Machines algorithm was applied. In addition, individuals of Iberian wild pear were discriminated with probability of over 55%, when the Maximum Likelihood algorithm was applied. From the perspective of improving the sampling effort, these results are a starting point for facilitating research on the abundance, distribution and spatial structure of P. bourgaeana at different scales, in order to quantify the conservation status of this species.<\/jats:p>","DOI":"10.3390\/f5061304","type":"journal-article","created":{"date-parts":[[2014,6,11]],"date-time":"2014-06-11T11:59:22Z","timestamp":1402487962000},"page":"1304-1330","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Evaluation and Comparison of QuickBird and ADS40-SH52 Multispectral Imagery for Mapping Iberian Wild Pear Trees (Pyrus bourgaeana, Decne) in a Mediterranean Mixed Forest"],"prefix":"10.3390","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8671-4968","authenticated-orcid":false,"given":"Salvador","family":"Arenas-Castro","sequence":"first","affiliation":[{"name":"Department of Land Use and Improvement, Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kam\u00fdck\u00e1 129, 165 21 Prague 6 (Suchdol), Czech Republic"}]},{"given":"Juan","family":"Fern\u00e1ndez-Haeger","sequence":"additional","affiliation":[{"name":"Department of Botany, Ecology and Plant Physiology (Area of Ecology), Faculty of Sciences, University of Cordoba, Cordoba 14071, Spain"}]},{"given":"Diego","family":"Jordano-Barbudo","sequence":"additional","affiliation":[{"name":"Department of Botany, Ecology and Plant Physiology (Area of Ecology), Faculty of Sciences, University of Cordoba, Cordoba 14071, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2014,6,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1093\/jpe\/rtm005","article-title":"Remote Sensing Imagery in Vegetation Mapping: A review","volume":"1","author":"Xie","year":"2008","journal-title":"J. Plant. Ecol."},{"key":"ref_2","first-page":"49","article-title":"A Framework for Mapping Tree Species Combining Hyperspectral and LiDAR Data: Role of Selected Classifiers and Sensor across Three Spatial Scales","volume":"26","author":"Ghosh","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2377","DOI":"10.1080\/01431160117096","article-title":"Review article. Using Remote Sensing to Assess Biodiversity","volume":"22","author":"Nagendra","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1641\/0006-3568(2004)054[0511:HSRRSD]2.0.CO;2","article-title":"High Spatial Resolution Remotely Sensed Data for Ecosystem Characterization","volume":"4","author":"Wulder","year":"2004","journal-title":"Bioscience"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1301","DOI":"10.1109\/TGRS.2007.912448","article-title":"Synthesis of Multispectral Images to High Spatial Resolution: A Critical Review of Fusion Methods Based on Remote Sensing Physics","volume":"46","author":"Thomas","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/S0098-3004(00)00110-2","article-title":"TIDA: An Algorithm for the Delineation of Tree Crowns in High Spatial Resolution Remotely Sensed Imagery","volume":"28","author":"Culvenor","year":"2002","journal-title":"Comput. Geosci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1007\/s10661-007-9807-y","article-title":"Mapping Giant Salvinia with Satellite Imagery and Image Analysis","volume":"139","author":"Everitt","year":"2008","journal-title":"Environ. Monit. Assess."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/S0034-4257(00)00101-2","article-title":"Local Maximum Filtering for the Extraction of Tree Location and Basal Area from High Spatial Resolution Imagery","volume":"73","author":"Wulder","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2225","DOI":"10.1080\/01431160310001659252","article-title":"Comparison of Airborne and Satellite High Spatial Resolution Data for the Identification of Individual Trees with Local Maxima Filtering","volume":"10","author":"Wulder","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.jenvman.2004.10.002","article-title":"Techniques for Accuracy Assessment of Tree Locations Extracted From Remotely Sensed Imagery","volume":"74","author":"Nelson","year":"2005","journal-title":"J. Environ. Manage."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1080\/10635150252899806","article-title":"Mapping Spatial Pattern in Biodiversity for Regional Conservation Planning: Where to from Here?","volume":"51","author":"Ferrier","year":"2002","journal-title":"Syst. Biol."},{"key":"ref_12","unstructured":"Heller, R.C., Doverspike, G.E., and Aldrich, R.C. (1964). Identification of Tree Species on Large Scale Panchromatic and Color Aerial Photographs, Department of Agriculture."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/j.rse.2004.04.006","article-title":"Species Classification of Individually Segmented Tree Crowns in High-Resolution Aerial Images Using Radiometric and Morphologic Image Measures","volume":"91","author":"Erikson","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1080\/10106040701337543","article-title":"Mapping Spiny Aster Infestations with QuickBird Imagery","volume":"22","author":"Everitt","year":"2007","journal-title":"Geocarto. Int."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/j.rse.2005.03.009","article-title":"Hyperspectral Discrimination of Tropical Rain Forest Tree Species at Leaf to Crown Scales","volume":"96","author":"Clark","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1016\/j.rse.2005.10.014","article-title":"Mapping Invasive Plants using Hyperspectral Imagery and Breiman Culter Classifications (randomForest)","volume":"100","author":"Lawrence","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1016\/j.rse.2007.02.029","article-title":"Single Tree Detection in Very High Resolution Remote Sensing Data","volume":"110","author":"Hirschmugl","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.rse.2010.08.006","article-title":"Semi-automatic Classification of Tree Species in Different Forest Ecosystems by Spectral and Geometric Variables Derived from Airborne Digital Sensor (ADS40) and RC30 Data","volume":"115","author":"Waser","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1111\/j.1477-9730.2007.00446.x","article-title":"Airborne Digital Imaging Technology: A New Overview","volume":"22","author":"Petrie","year":"2007","journal-title":"Photogramm. Rec."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/S0034-4257(00)00159-0","article-title":"A Comparison of Multispectral and Multitemporal Information in High Spatial Resolution Imagery for Classification of Individual Tree Species in A Temperate Hardwood Forest","volume":"75","author":"Key","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_21","first-page":"152","article-title":"Exploring Full-Waveform LiDAR Parameters for Tree Species Classification","volume":"13","author":"Heinzel","year":"2011","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1016\/S0165-0114(02)00049-0","article-title":"Individual Tree-Based Species Classification in High Spatial Resolution Aerial Images of Forests using Fuzzy Sets","volume":"132","author":"Brandtberg","year":"2002","journal-title":"Fuzzy Sets Syst."},{"key":"ref_23","first-page":"101","article-title":"Investigating Multiple Data Sources for Tree Species Classification in Temperate Forest and Use for Single Tree Delineation","volume":"18","author":"Heinzel","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2632","DOI":"10.1109\/TGRS.2012.2216272","article-title":"Tree Species Classification in Boreal Forests with Hyperspectral Data","volume":"51","author":"Dalponte","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sensing."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1007\/s10661-006-9407-2","article-title":"Canopy Spectra and Remote Sensing of Ashe Juniper and Associated Vegetation","volume":"130","author":"Everitt","year":"2007","journal-title":"Environ. Monit. Assess."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.isprsjprs.2013.03.007","article-title":"Spectral Discrimination of Giant Reed (Arundo. donax, L.): A Seasonal Study in Riparian Areas","volume":"80","author":"Fernandes","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/S0378-1127(00)00383-2","article-title":"Forests of the Mediterranean Region: Gaps in Knowledge and Research Needs","volume":"132","author":"Oswald","year":"2000","journal-title":"For. Ecol. Manage."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.foreco.2005.10.056","article-title":"Estimation of Tree Canopy cover in Evergreen Oak Woodlands using Remote Sensing","volume":"223","author":"Carreiras","year":"2006","journal-title":"For. Ecol. Manag."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3113","DOI":"10.1080\/01431160310001654978","article-title":"Mapping Mediterranean scrub with Satellite Imagery: Biomass Estimation and Spectral Behavior","volume":"25","author":"Calvao","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.rse.2011.12.024","article-title":"Modeling Plant Species Richness using Reflectance and Texture Data Derived from QuickBird in A Recently Burned Area of Central Spain","volume":"119","author":"Viedma","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"112","DOI":"10.2307\/2399957","article-title":"Hot-spots Analysis for Conservation of Plant Biodiversity in the Mediterranean Basin","volume":"84","year":"1997","journal-title":"Ann. Mo. Bot. Gard."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1038\/35002501","article-title":"Biodiversity Hotspots for Conservation Priorities","volume":"403","author":"Myers","year":"2000","journal-title":"Nature"},{"key":"ref_33","unstructured":"Arenas-Castro, S. An\u00e1lisis de la estructura de una poblaci\u00f3n de Piru\u00e9tano (Pyrus. bourgaeana, Decne) basado en t\u00e9cnicas de Teledetecci\u00f3n y SIG. Available online:http:\/\/hdl.handle.net\/10396\/7832."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"311","DOI":"10.2980\/16-3-3253","article-title":"Seed Dispersal in the Iberian Pear Pyrus. bourgaeana: A Role for Infrequent Mutualists","volume":"16","author":"Fedriani","year":"2009","journal-title":"Ecoscience"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1111\/j.1600-0587.2009.06052.x","article-title":"Spatial Pattern of Adult Trees and the Mammal-Generated Seed Rain in the Iberian Pear","volume":"33","author":"Fedriani","year":"2010","journal-title":"Ecography"},{"key":"ref_36","first-page":"143","article-title":"The Genus Pyrus. L. (Rosaceae.) in South-West Europe and North Africa","volume":"121","author":"Aldasoro","year":"1996","journal-title":"Bot. J. Linn. Soc."},{"key":"ref_37","first-page":"1","article-title":"Mapping Wild Pear Trees (Pyrus bourgaeana) in Mediterranean Forest using High Resolution QuickBird Satellite Imagery","volume":"34","author":"Julien","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_38","unstructured":"ENVI FLAASH. (2009). Atmospheric Correction Module, Spectral Sciences Incorporated (SSI)."},{"key":"ref_39","unstructured":"Haydan, R., Dalke, G.W., Henkel, J., and Bare, J.E. (1982, January 19\u201325). Applications of the IHS Colour Transform to the Processing of Multisensor Data and Image Enhancement. Proceedings of the International Symposium on Remote Sensing of Arid and Semi-Arid Lands, Cairo, Egypt."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"725","DOI":"10.1080\/01431160110040323","article-title":"An Assessment of Support Vector Machines for Land Cover Classification","volume":"23","author":"Huang","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_41","unstructured":"Cortes, C., and Vapnik, V. (1995). Kluwer Academic Publisher."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.isprsjprs.2010.11.001","article-title":"Support Vector Machines in Remote Sensing: A Review","volume":"66","author":"Mountrakis","year":"2011","journal-title":"ISPRS-J. Photogramm. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1778","DOI":"10.1109\/TGRS.2004.831865","article-title":"Classification of Hyperspectral Remote Sensing Images with Support Vector Machines","volume":"42","author":"Melgani","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_44","unstructured":"(2010). Exelis Visual Information Solutions, The Environment for Visualizing Images (ENVI). version 4.6."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"17131","DOI":"10.1029\/97JD00201","article-title":"Atmospheric Correction of Visible to Middle-Infrared EOS-MODIS Data over Land Surfaces: Background, Operational Algorithm and Validation","volume":"102","author":"Vermote","year":"1997","journal-title":"J. Geophys. Res."},{"key":"ref_46","unstructured":"Digitalglobe, Inc. (2007). Radiometric Radiance Conversion for QB Data, Digitalglobe, Inc."},{"key":"ref_47","first-page":"1","article-title":"Absolute Spectroradiometric Calibration of the ADS40 Sensor","volume":"36","author":"Beisl","year":"2006","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Congalton, R.G., and Green, K. (2009). Assessing the Accuracy of Remotely Sensed Data\u2014Principles and Practices, CRC Press, Taylor & Francis Group.","DOI":"10.1201\/9781420055139"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"5273","DOI":"10.1080\/01431160903130937","article-title":"Sample Size Determination for Image Classification Accuracy Assessment and Comparison","volume":"30","author":"Foody","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/S0034-4257(97)00164-8","article-title":"Progressive Two-Class Decision Classifier for Optimization of Class Discriminations","volume":"63","author":"Jia","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1007\/s11004-008-9156-6","article-title":"An Objective Analysis of Support Vector Machine Based Classification for Remote Sensing","volume":"40","author":"Oommen","year":"2008","journal-title":"Math. Geosci."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1335","DOI":"10.1109\/TGRS.2004.827257","article-title":"A Relative Evaluation of Multiclass Image Classification by Support Vector Machines","volume":"42","author":"Foody","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1109\/72.991427","article-title":"A Comparison of Methods for Multiclass Support Vector Machines","volume":"13","author":"Hsu","year":"2002","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"2731","DOI":"10.1016\/j.patcog.2008.04.013","article-title":"Statistical Pattern Recognition in Remote Sensing","volume":"41","author":"Chen","year":"2008","journal-title":"Pattern Recognit."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/S0034-4257(97)00083-7","article-title":"Selecting and Interpreting Measures of Thematic Classification Accuracy","volume":"62","author":"Stehman","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/0034-4257(91)90048-B","article-title":"A Review of Assessing the Accuracy of Classifications of Remotely Sensed Data","volume":"37","author":"Congalton","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"4407","DOI":"10.1080\/01431161.2011.552923","article-title":"Death to Kappa: Birth of Quantity Disagreement and Allocation Disagreement for Accuracy Assessment","volume":"32","author":"Pontius","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Agresti, A. (2007). An Introduction to Categorical Data Analysis, Wiley-Interscience. [2nd ed.].","DOI":"10.1002\/0470114754"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1080\/01431160500275762","article-title":"Comparing Accuracy Assessments to Infer Superiority of Image Classification Methods","volume":"27","author":"Jia","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"627","DOI":"10.14358\/PERS.70.5.627","article-title":"Thematic Map Comparison: Evaluating the Statistical Significance of Differences in Classification Accuracy","volume":"70","author":"Foody","year":"2004","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1239","DOI":"10.1109\/83.935039","article-title":"New Methods for Dynamic Mosaicking","volume":"10","author":"Nicolas","year":"2001","journal-title":"IEEE Trans. Image Process."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1007\/s00138-007-0114-y","article-title":"An Efficient Image-Mosaicing Method Based on Multifeature Matching","volume":"20","author":"Zagrouba","year":"2009","journal-title":"Mach. Vis. Appl."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1080\/01431160512331314083","article-title":"Support Vector Machines for Classification in Remote Sensing","volume":"26","author":"Pal","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_64","unstructured":"Arenas-Castro, S., Sobrino, J.A., Fern\u00e1ndez-Haeger, J., and Jordano-Barbudo, D. (2013). Spectral Discrimination of Wild Pear (Pyrus bourgaeana, D.), A Rare Mediterranean Tree in Sierra Morena (Andalusia, Spain), submitted."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1007\/s10661-007-9619-0","article-title":"Mapping Broom Snakeweed through Image Analysis of Color-Infrared Photography and Digital Imagery","volume":"134","author":"Everitt","year":"2007","journal-title":"Environ. Monit. Assess."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/S0034-4257(02)00196-7","article-title":"Spectral Discrimination of Vegetation Types in A Coastal Wetland","volume":"85","author":"Schmidt","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1016\/j.rse.2007.02.030","article-title":"Single Tree Species Classification with a Hypothetical Multi-Spectral Satellite","volume":"110","author":"Larsen","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/j.rse.2004.10.011","article-title":"Automated Tree Recognition in Old Growth Conifer Stands with High Resolution Digital Imagery","volume":"94","author":"Leckie","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"135","DOI":"10.14358\/PERS.70.1.135","article-title":"Exploitation of Very High Resolution Satellite Data for Tree Species Identification","volume":"70","author":"Carleer","year":"2004","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.isprsjprs.2003.09.007","article-title":"Object-Based Classification of Remote Sensing Data for Change Detection","volume":"58","author":"Walter","year":"2004","journal-title":"ISPRS J. Photogramm. Remote Sens."}],"container-title":["Forests"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4907\/5\/6\/1304\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:12:20Z","timestamp":1760217140000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4907\/5\/6\/1304"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,6,11]]},"references-count":70,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2014,6]]}},"alternative-id":["f5061304"],"URL":"https:\/\/doi.org\/10.3390\/f5061304","relation":{},"ISSN":["1999-4907"],"issn-type":[{"type":"electronic","value":"1999-4907"}],"subject":[],"published":{"date-parts":[[2014,6,11]]}}}